codacy-code-review

A code-review helper that adds Codacy's checks to pull requests. Codacy is a service that scans code for quality problems, security risks, test coverage, and duplicated code.

In plain words
What is it for?
Use it to review pull requests, check their coverage and quality, and find new security or code-quality issues.
Why use it?
It gives reviewers extra evidence about what changed without requiring them to find each problem manually. It also shows which findings are new in the pull request.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/codacy/codacy-skills/codacy-code-review
Any agent
npx skills add codacy/codacy-skills --skill codacy-code-review
Clone the repo
git clone --depth 1 https://github.com/codacy/codacy-skills

Made for: Claude Code, Codex.

Per session 117 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,073 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00117 $0.02073
Opus 5 $0.00059 $0.01037
Sonnet 5 $0.00023 $0.00415
Haiku 4.5 $0.00012 $0.00207

Measured 2d ago against content hash 0c0d8e0d756d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

codacy-code-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/codacy-code-review/SKILL.md · 191 lines

How it starts

The opening of the file, as written. The whole thing — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Codacy Code Review

Glossary: See glossary.md for shared definitions of Codacy concepts (issues, findings, severity, coverage, tools, patterns, etc.).

This skill enriches code reviews with Codacy data. It works alongside any existing code review process (a code-review skill, CodeRabbit, manual review, etc.) — it adds Codacy-specific data on top.

Prerequisites

  • Codacy Analysis CLI (codacy-analysis) — for fast local analysis. See codacy-analysis-cli for setup.
  • Codacy Cloud CLI (codacy) — for coverage data, quality gate status, and ignoring issues. See codacy-cloud-cli for setup.

Both CLIs share credentials at ~/.codacy/credentials, so a single login covers both.

Local vs Cloud analysis

This skill uses two complementary analysis sources:

Source What it provides Speed
Analysis CLI (local) Issues and security findings on PR changes Instant — no push or remote analysis needed
Cloud CLI (remote) Coverage delta, quality gate, duplication, issue management (ignore/unignore) Requires the PR to be pushed and analyzed by Codacy

Prefer local analysis for issue detection — it runs immediately on the current working tree with --pr and doesn't require waiting for remote analysis. Use the Cloud CLI to supplement with coverage data and quality gate status, and to manage issues (ignore/unignore).

The Analysis CLI may not support every tool that Codacy Cloud runs. If the project uses tools not available locally (check with codacy-analysis analyze --inspect --output-format json), flag that some findings may only appear in the Cloud results.

How Codacy PR data works

  • Cloud data reflects the HEAD commit of the PR — the remote analysis shown is always for the latest push to the PR branch, not a specific commit.
  • Local analysis reflects the working treecodacy-analysis analyze --pr compares the current branch against the PR's target branch, catching issues even before pushing.
  • Ignoring issues is a Cloud-only operation — it takes effect immediately on Codacy but any other configuration changes (patterns, tools) only apply after the next remote analysis.
  • Stale or missing remote analysis — if the Cloud PR analysis appears outdated or incomplete, use codacy pull-request <provider> <org> <repo> <prNumber> --reanalyze-and-wait to trigger reanalysis and block until it completes (polls every 10 seconds, up to 20 minutes). For fire-and-forget, use --reanalyze instead and re-check manually.
  • Auto-detection — when running inside the repo, the Cloud CLI auto-detects provider/org/repo from the git remote. Commands like codacy pull-request <prNumber> work without explicit parameters.

Read the full file on GitHub · 191 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 191 lines · 117 tokens per session scan A 0c0d8e0d756d

Subscribe to this mod's changes

codacy-code-review is a skill published in the GitHub repository codacy/codacy-skills (11 stars, last pushed 1mo ago), licensed MIT. It adds 117 tokens to every session and 2,073 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

babysit-pr

Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…

openai/codex · 114 tokens

imagegen

Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…

openai/codex · 113 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens